from sklearn_benchmarks.reporting.hp_match import HPMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = HPMatchReporting("sklearnex", config="config.yml")
reporting.make_report()
KNeighborsClassifier_brute_force¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.014 | 0.001 | NaN | 5.631 | 0.0 | -1 | 1 | NaN | NaN | 0.059 | 0.005 | 0.241 | 0.242 | See | See |
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.014 | 0.001 | NaN | 5.613 | 0.0 | -1 | 5 | NaN | NaN | 0.057 | 0.001 | 0.249 | 0.249 | See | See |
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.014 | 0.001 | NaN | 5.692 | 0.0 | 1 | 100 | NaN | NaN | 0.057 | 0.001 | 0.248 | 0.248 | See | See |
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.014 | 0.001 | NaN | 5.738 | 0.0 | -1 | 100 | NaN | NaN | 0.057 | 0.002 | 0.244 | 0.244 | See | See |
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.014 | 0.001 | NaN | 5.576 | 0.0 | 1 | 5 | NaN | NaN | 0.057 | 0.001 | 0.252 | 0.252 | See | See |
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.015 | 0.001 | NaN | 5.267 | 0.0 | 1 | 1 | NaN | NaN | 0.057 | 0.001 | 0.268 | 0.268 | See | See |
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | NaN | 0.330 | 0.0 | -1 | 1 | NaN | NaN | 0.009 | 0.000 | 0.554 | 0.555 | See | See |
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | NaN | 0.300 | 0.0 | -1 | 5 | NaN | NaN | 0.010 | 0.000 | 0.562 | 0.562 | See | See |
| 24 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | NaN | 0.332 | 0.0 | 1 | 100 | NaN | NaN | 0.009 | 0.001 | 0.514 | 0.515 | See | See |
| 27 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | NaN | 0.337 | 0.0 | -1 | 100 | NaN | NaN | 0.010 | 0.001 | 0.499 | 0.500 | See | See |
| 30 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | NaN | 0.326 | 0.0 | 1 | 5 | NaN | NaN | 0.009 | 0.000 | 0.537 | 0.538 | See | See |
| 33 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.001 | NaN | 0.339 | 0.0 | 1 | 1 | NaN | NaN | 0.010 | 0.001 | 0.483 | 0.485 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.287 | 0.096 | NaN | 0.0 | 0.002 | -1 | 1 | 0.663 | 0.687 | 0.472 | 0.023 | 4.849 | 4.854 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.027 | 0.003 | NaN | 0.0 | 0.027 | -1 | 1 | 1.000 | 1.000 | 0.012 | 0.001 | 2.341 | 2.350 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 3.151 | 0.049 | NaN | 0.0 | 0.003 | -1 | 5 | 0.757 | 0.742 | 0.466 | 0.009 | 6.759 | 6.760 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.029 | 0.002 | NaN | 0.0 | 0.029 | -1 | 5 | 1.000 | 1.000 | 0.011 | 0.001 | 2.642 | 2.646 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.536 | 0.050 | NaN | 0.0 | 0.003 | 1 | 100 | 0.882 | 0.875 | 0.521 | 0.004 | 4.865 | 4.865 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.028 | 0.004 | NaN | 0.0 | 0.028 | 1 | 100 | 1.000 | 0.000 | 0.013 | 0.003 | 2.120 | 2.160 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 3.182 | 0.056 | NaN | 0.0 | 0.003 | -1 | 100 | 0.882 | 0.875 | 0.519 | 0.006 | 6.129 | 6.129 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.028 | 0.003 | NaN | 0.0 | 0.028 | -1 | 100 | 1.000 | 0.000 | 0.012 | 0.002 | 2.364 | 2.390 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.518 | 0.027 | NaN | 0.0 | 0.003 | 1 | 5 | 0.757 | 0.742 | 0.460 | 0.006 | 5.470 | 5.470 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.026 | 0.001 | NaN | 0.0 | 0.026 | 1 | 5 | 1.000 | 1.000 | 0.011 | 0.001 | 2.311 | 2.325 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.626 | 0.013 | NaN | 0.0 | 0.002 | 1 | 1 | 0.663 | 0.687 | 0.467 | 0.010 | 3.481 | 3.482 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.025 | 0.001 | NaN | 0.0 | 0.025 | 1 | 1 | 1.000 | 1.000 | 0.011 | 0.000 | 2.271 | 2.273 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.839 | 0.051 | NaN | 0.0 | 0.002 | -1 | 1 | 0.896 | 0.967 | 0.103 | 0.004 | 17.911 | 17.924 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.007 | 0.002 | NaN | 0.0 | 0.007 | -1 | 1 | 1.000 | 1.000 | 0.001 | 0.000 | 10.524 | 10.585 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.782 | 0.028 | NaN | 0.0 | 0.003 | -1 | 5 | 0.922 | 0.974 | 0.104 | 0.001 | 26.876 | 26.878 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.009 | 0.005 | NaN | 0.0 | 0.009 | -1 | 5 | 1.000 | 1.000 | 0.001 | 0.000 | 12.055 | 12.366 | See | See |
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.210 | 0.012 | NaN | 0.0 | 0.002 | 1 | 100 | 0.929 | 0.975 | 0.161 | 0.003 | 13.701 | 13.703 | See | See |
| 26 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | NaN | 0.0 | 0.003 | 1 | 100 | 1.000 | 1.000 | 0.001 | 0.000 | 4.469 | 4.520 | See | See |
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.816 | 0.036 | NaN | 0.0 | 0.003 | -1 | 100 | 0.929 | 0.975 | 0.170 | 0.012 | 16.519 | 16.561 | See | See |
| 29 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.008 | 0.003 | NaN | 0.0 | 0.008 | -1 | 100 | 1.000 | 1.000 | 0.001 | 0.000 | 10.113 | 10.153 | See | See |
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.207 | 0.016 | NaN | 0.0 | 0.002 | 1 | 5 | 0.922 | 0.974 | 0.106 | 0.003 | 20.905 | 20.912 | See | See |
| 32 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | NaN | 0.0 | 0.003 | 1 | 5 | 1.000 | 1.000 | 0.001 | 0.000 | 5.072 | 5.139 | See | See |
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.308 | 0.018 | NaN | 0.0 | 0.001 | 1 | 1 | 0.896 | 0.967 | 0.102 | 0.002 | 12.830 | 12.832 | See | See |
| 35 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.002 | 0.000 | NaN | 0.0 | 0.002 | 1 | 1 | 1.000 | 1.000 | 0.001 | 0.000 | 3.290 | 3.323 | See | See |
KNeighborsClassifier_kd_tree¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.087 | 0.059 | NaN | 0.026 | 0.0 | -1 | 1 | NaN | NaN | 0.981 | 0.287 | 3.147 | 3.279 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.938 | 0.060 | NaN | 0.020 | 0.0 | -1 | 5 | NaN | NaN | 0.883 | 0.012 | 4.459 | 4.459 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.881 | 0.107 | NaN | 0.021 | 0.0 | 1 | 100 | NaN | NaN | 0.889 | 0.010 | 4.368 | 4.368 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.896 | 0.059 | NaN | 0.021 | 0.0 | -1 | 100 | NaN | NaN | 0.900 | 0.024 | 4.331 | 4.333 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.845 | 0.070 | NaN | 0.021 | 0.0 | 1 | 5 | NaN | NaN | 0.893 | 0.013 | 4.305 | 4.305 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.899 | 0.123 | NaN | 0.021 | 0.0 | 1 | 1 | NaN | NaN | 0.904 | 0.018 | 4.314 | 4.314 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.001 | NaN | 0.015 | 0.0 | -1 | 1 | NaN | NaN | 0.005 | 0.003 | 0.231 | 0.286 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.023 | 0.0 | -1 | 5 | NaN | NaN | 0.002 | 0.001 | 0.453 | 0.589 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.025 | 0.0 | 1 | 100 | NaN | NaN | 0.002 | 0.001 | 0.356 | 0.435 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.026 | 0.0 | -1 | 100 | NaN | NaN | 0.001 | 0.000 | 0.570 | 0.571 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.024 | 0.0 | 1 | 5 | NaN | NaN | 0.001 | 0.000 | 0.606 | 0.607 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | NaN | 0.025 | 0.0 | 1 | 1 | NaN | NaN | 0.001 | 0.000 | 0.595 | 0.596 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.987 | 1.294 | NaN | 0.000 | 0.001 | -1 | 1 | 0.929 | 0.910 | 0.128 | 0.006 | 7.743 | 7.751 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | NaN | 0.000 | 0.003 | -1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 10.580 | 10.853 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.147 | 0.474 | NaN | 0.000 | 0.001 | -1 | 5 | 0.946 | 0.941 | 0.232 | 0.004 | 4.952 | 4.953 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.004 | 0.001 | NaN | 0.000 | 0.004 | -1 | 5 | 1.000 | 1.000 | 0.001 | 0.000 | 6.598 | 6.810 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 5.905 | 0.750 | NaN | 0.000 | 0.006 | 1 | 100 | 0.951 | 0.940 | 0.708 | 0.014 | 8.336 | 8.338 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | NaN | 0.000 | 0.003 | 1 | 100 | 1.000 | 1.000 | 0.001 | 0.001 | 2.724 | 3.193 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 3.249 | 0.417 | NaN | 0.000 | 0.003 | -1 | 100 | 0.951 | 0.940 | 0.708 | 0.011 | 4.586 | 4.587 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.005 | 0.001 | NaN | 0.000 | 0.005 | -1 | 100 | 1.000 | 1.000 | 0.001 | 0.001 | 4.910 | 5.441 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.827 | 0.469 | NaN | 0.000 | 0.002 | 1 | 5 | 0.946 | 0.941 | 0.243 | 0.011 | 7.519 | 7.526 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.000 | NaN | 0.000 | 0.002 | 1 | 5 | 1.000 | 1.000 | 0.001 | 0.000 | 2.966 | 3.089 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.016 | 0.402 | NaN | 0.000 | 0.001 | 1 | 1 | 0.929 | 0.910 | 0.131 | 0.005 | 7.737 | 7.742 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 3.508 | 3.653 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.040 | 0.016 | NaN | 0.000 | 0.000 | -1 | 1 | 0.891 | 0.879 | 0.001 | 0.000 | 67.926 | 68.156 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | -1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 17.069 | 17.720 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.035 | 0.004 | NaN | 0.000 | 0.000 | -1 | 5 | 0.911 | 0.905 | 0.001 | 0.000 | 38.489 | 38.708 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | -1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 18.272 | 18.480 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.049 | 0.016 | NaN | 0.000 | 0.000 | 1 | 100 | 0.894 | 0.917 | 0.007 | 0.001 | 6.842 | 6.970 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 4.650 | 4.881 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.050 | 0.008 | NaN | 0.000 | 0.000 | -1 | 100 | 0.894 | 0.917 | 0.007 | 0.002 | 7.503 | 7.739 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.000 | NaN | 0.000 | 0.003 | -1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 17.975 | 18.125 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.031 | 0.001 | NaN | 0.001 | 0.000 | 1 | 5 | 0.911 | 0.905 | 0.001 | 0.000 | 34.364 | 34.397 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 5.178 | 5.358 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.030 | 0.001 | NaN | 0.001 | 0.000 | 1 | 1 | 0.891 | 0.879 | 0.001 | 0.000 | 52.625 | 52.651 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | NaN | 0.000 | 0.001 | 1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 6.169 | 6.221 | See | See |
KMeans_tall¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter_sklearn | iteration_throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.651 | 0.089 | 30 | 0.025 | 0.0 | random | NaN | 30 | NaN | 0.331 | 0.015 | 1.964 | 1.966 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.697 | 0.018 | 30 | 0.023 | 0.0 | k-means++ | NaN | 30 | NaN | 0.372 | 0.016 | 1.871 | 1.873 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 7.811 | 0.257 | 30 | 0.102 | 0.0 | random | NaN | 30 | NaN | 4.299 | 0.092 | 1.817 | 1.818 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 8.192 | 0.031 | 30 | 0.098 | 0.0 | k-means++ | NaN | 30 | NaN | 4.493 | 0.033 | 1.823 | 1.823 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter_sklearn | iteration_throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.001 | 30 | 0.007 | 0.000 | random | 0.001 | 30 | 0.001 | 0.0 | 0.0 | 8.870 | 11.128 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | random | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 13.399 | 13.559 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.000 | 30 | 0.008 | 0.000 | k-means++ | 0.001 | 30 | 0.001 | 0.0 | 0.0 | 8.274 | 8.507 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | k-means++ | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 10.205 | 10.757 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.000 | 30 | 0.380 | 0.000 | random | 0.001 | 30 | 0.002 | 0.0 | 0.0 | 6.389 | 6.724 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | random | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 10.570 | 10.666 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.000 | 30 | 0.370 | 0.000 | k-means++ | 0.002 | 30 | 0.002 | 0.0 | 0.0 | 6.461 | 6.688 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.000 | 30 | 0.000 | 0.002 | k-means++ | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 9.962 | 10.100 | See | See |
KMeans_short¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter_sklearn | iteration_throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 0.110 | 0.002 | 20 | 0.001 | 0.0 | random | NaN | 20 | NaN | 0.057 | 0.002 | 1.922 | 1.924 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 0.331 | 0.007 | 20 | 0.000 | 0.0 | k-means++ | NaN | 20 | NaN | 0.147 | 0.002 | 2.257 | 2.257 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 0.359 | 0.006 | 20 | 0.022 | 0.0 | random | NaN | 20 | NaN | 0.288 | 0.008 | 1.249 | 1.249 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 1.206 | 0.015 | 20 | 0.007 | 0.0 | k-means++ | NaN | 20 | NaN | 0.659 | 0.010 | 1.830 | 1.830 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter_sklearn | iteration_throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.000 | 20 | 0.007 | 0.000 | random | 0.000 | 20 | -0.001 | 0.001 | 0.0 | 3.515 | 3.526 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | random | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 11.361 | 11.422 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.000 | 20 | 0.007 | 0.000 | k-means++ | 0.001 | 20 | -0.001 | 0.001 | 0.0 | 3.309 | 3.329 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | k-means++ | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 10.422 | 10.648 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 0.004 | 0.001 | 20 | 0.215 | 0.000 | random | 0.279 | 20 | 0.294 | 0.002 | 0.0 | 2.282 | 2.283 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | random | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 8.500 | 8.832 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 0.004 | 0.001 | 20 | 0.195 | 0.000 | k-means++ | 0.317 | 20 | 0.257 | 0.002 | 0.0 | 2.521 | 2.523 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.000 | 20 | 0.000 | 0.002 | k-means++ | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 8.278 | 8.677 | See | See |
LogisticRegression¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | 17.705 | 0.406 | [20] | 0.045 | 0.000 | NaN | NaN | NaN | NaN | NaN | 3.136 | 0.018 | 5.646 | 5.646 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | 1.579 | 0.651 | [26] | 0.051 | 0.002 | NaN | NaN | NaN | NaN | NaN | 1.304 | 0.036 | 1.211 | 1.212 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 0.001 | 0.001 | [20] | 1.198 | 0.0 | NaN | NaN | NaN | NaN | 0.56 | 0.001 | 0.001 | 0.743 | 1.404 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | 0.000 | 0.000 | [20] | 0.009 | 0.0 | NaN | NaN | NaN | NaN | 1.00 | 0.000 | 0.000 | 0.353 | 0.355 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 0.003 | 0.000 | [26] | 3.178 | 0.0 | NaN | NaN | NaN | NaN | 0.35 | 0.007 | 0.001 | 0.346 | 0.348 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | 0.000 | 0.000 | [26] | 0.623 | 0.0 | NaN | NaN | NaN | NaN | 0.00 | 0.002 | 0.000 | 0.065 | 0.065 | See | See |
Ridge¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | max_iter | random_state | r2_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | 0.334 | 0.011 | NaN | 0.239 | 0.0 | NaN | NaN | NaN | 0.344 | 0.018 | 0.971 | 0.972 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | 1.476 | 0.108 | NaN | 0.542 | 0.0 | NaN | NaN | NaN | 0.496 | 0.239 | 2.974 | 3.302 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | max_iter | random_state | r2_score | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 0.012 | 0.001 | NaN | 6.661 | 0.0 | NaN | NaN | 0.083 | 0.02 | 0.001 | 0.587 | 0.588 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | 0.000 | 0.000 | NaN | 0.833 | 0.0 | NaN | NaN | NaN | 0.00 | 0.000 | 0.647 | 0.665 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | 0.000 | 0.000 | NaN | 4.653 | 0.0 | NaN | NaN | 1.000 | 0.00 | 0.000 | 0.431 | 0.679 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | 0.000 | 0.000 | NaN | 0.010 | 0.0 | NaN | NaN | NaN | 0.00 | 0.000 | 0.568 | 0.602 | See | See |